import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


_UpperCAmelCase          =						logging.get_logger(__name__)

_UpperCAmelCase          =						"""▁"""

_UpperCAmelCase          =						{"""vocab_file""": """sentencepiece.bpe.model"""}

_UpperCAmelCase          =						{
    """vocab_file""": {
        """facebook/mbart-large-50-one-to-many-mmt""": (
            """https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model"""
        ),
    }
}

_UpperCAmelCase          =						{
    """facebook/mbart-large-50-one-to-many-mmt""": 1024,
}

# fmt: off
_UpperCAmelCase          =						["""ar_AR""", """cs_CZ""", """de_DE""", """en_XX""", """es_XX""", """et_EE""", """fi_FI""", """fr_XX""", """gu_IN""", """hi_IN""", """it_IT""", """ja_XX""", """kk_KZ""", """ko_KR""", """lt_LT""", """lv_LV""", """my_MM""", """ne_NP""", """nl_XX""", """ro_RO""", """ru_RU""", """si_LK""", """tr_TR""", """vi_VN""", """zh_CN""", """af_ZA""", """az_AZ""", """bn_IN""", """fa_IR""", """he_IL""", """hr_HR""", """id_ID""", """ka_GE""", """km_KH""", """mk_MK""", """ml_IN""", """mn_MN""", """mr_IN""", """pl_PL""", """ps_AF""", """pt_XX""", """sv_SE""", """sw_KE""", """ta_IN""", """te_IN""", """th_TH""", """tl_XX""", """uk_UA""", """ur_PK""", """xh_ZA""", """gl_ES""", """sl_SI"""]





class UpperCAmelCase		(   __A    ):


				'''simple docstring'''






				lowerCamelCase_        =   VOCAB_FILES_NAMES
				lowerCamelCase_        =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowerCamelCase_        =   PRETRAINED_VOCAB_FILES_MAP
				lowerCamelCase_        =   ['''input_ids''', '''attention_mask''']

				lowerCamelCase_        =   []
				lowerCamelCase_        =   []
				def __init__(		self						,      lowercase						,      lowercase=None						,      lowercase=None						,      lowercase="</s>"						,      lowercase="</s>"						,      lowercase="<s>"						,      lowercase="<unk>"						,      lowercase="<pad>"						,      lowercase="<mask>"						,      lowercase = None						,      **lowercase						,      ):



						"""simple docstring"""





						A_						:							Tuple      = AddedToken(lowercase						,      lstrip=lowercase						,      rstrip=lowercase   ) if isinstance(lowercase						,      lowercase   ) else mask_token

						A_						:							Any      = {} if sp_model_kwargs is None else sp_model_kwargs

						A_						:							str      = kwargs.get('additional_special_tokens'						,      []   )
						kwargs["additional_special_tokens"] += [
						    code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
						]

						super().__init__(
						    src_lang=lowercase						,      tgt_lang=lowercase						,      eos_token=lowercase						,      unk_token=lowercase						,      sep_token=lowercase						,      cls_token=lowercase						,      pad_token=lowercase						,      mask_token=lowercase						,      sp_model_kwargs=self.sp_model_kwargs						,      **lowercase						,      )

						A_						:							str      = spm.SentencePieceProcessor(**self.sp_model_kwargs   )
						self.sp_model.Load(str(lowercase   )   )
						A_						:							Optional[int]      = vocab_file

						# Original fairseq vocab and spm vocab must be "aligned":
						# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
						# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
						# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
						# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

						# Mimic fairseq token-to-id alignment for the first 4 token
						A_						:							Any      = {'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

						# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
						A_						:							Optional[int]      = 1

						A_						:							Union[str, Any]      = len(self.sp_model   )
						A_						:							str      = {
						    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(lowercase   )
						}
						A_						:							int      = {v: k for k, v in self.lang_code_to_id.items()}
						A_						:							int      = len(self.sp_model   ) + len(self.lang_code_to_id   ) + self.fairseq_offset

						self.fairseq_tokens_to_ids.update(self.lang_code_to_id   )
						A_						:							Any      = {v: k for k, v in self.fairseq_tokens_to_ids.items()}

						A_						:							List[str]      = src_lang if src_lang is not None else 'en_XX'
						A_						:							List[Any]      = self.lang_code_to_id[self._src_lang]
						A_						:							Any      = tgt_lang
						self.set_src_lang_special_tokens(self._src_lang   )
				@property
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						return len(self.sp_model   ) + len(self.lang_code_to_id   ) + self.fairseq_offset + 1  # Plus 1 for the mask token
				@property
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						return self._src_lang
				@src_lang.setter
				def     lowerCAmelCase_  (		self						,      lowercase   ):



						"""simple docstring"""





						A_						:							Union[str, Any]      = new_src_lang
						self.set_src_lang_special_tokens(self._src_lang   )
				def __getstate__(		self   ):



						"""simple docstring"""





						A_						:							Any      = self.__dict__.copy()
						A_						:							List[Any]      = None
						return state
				def __setstate__(		self						,      lowercase   ):



						"""simple docstring"""





						A_						:							int      = d

						# for backward compatibility
						if not hasattr(self						,      'sp_model_kwargs'   ):
								A_						:							Any      = {}

						A_						:							Optional[Any]      = spm.SentencePieceProcessor(**self.sp_model_kwargs   )
						self.sp_model.Load(self.vocab_file   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						A_						:							Tuple      = {self.convert_ids_to_tokens(lowercase   ): i for i in range(self.vocab_size   )}
						vocab.update(self.added_tokens_encoder   )
						return vocab
				def     lowerCAmelCase_  (		self						,      lowercase   ):



						"""simple docstring"""





						return self.sp_model.encode(lowercase						,      out_type=lowercase   )
				def     lowerCAmelCase_  (		self						,      lowercase   ):



						"""simple docstring"""





						if token in self.fairseq_tokens_to_ids:
								return self.fairseq_tokens_to_ids[token]
						A_						:							Optional[int]      = self.sp_model.PieceToId(lowercase   )

						# Need to return unknown token if the SP model returned 0
						return spm_id + self.fairseq_offset if spm_id else self.unk_token_id
				def     lowerCAmelCase_  (		self						,      lowercase   ):



						"""simple docstring"""





						if index in self.fairseq_ids_to_tokens:
								return self.fairseq_ids_to_tokens[index]
						return self.sp_model.IdToPiece(index - self.fairseq_offset   )
				def     lowerCAmelCase_  (		self						,      lowercase   ):



						"""simple docstring"""





						A_						:							Any      = []
						A_						:							Optional[int]      = ''
						A_						:							List[Any]      = False
						for token in tokens:
								# make sure that special tokens are not decoded using sentencepiece model
								if token in self.all_special_tokens:
										if not prev_is_special:
												out_string += " "
										out_string += self.sp_model.decode(lowercase   ) + token
										A_						:							Tuple      = True
										A_						:							Dict      = []
								else:
										current_sub_tokens.append(lowercase   )
										A_						:							str      = False
						out_string += self.sp_model.decode(lowercase   )
						return out_string.strip()
				def     lowerCAmelCase_  (		self						,      lowercase						,      lowercase = None   ):



						"""simple docstring"""





						if not os.path.isdir(lowercase   ):
								logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''   )
								return
						A_						:							List[Any]      = os.path.join(
						    lowercase						,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )

						if os.path.abspath(self.vocab_file   ) != os.path.abspath(lowercase   ) and os.path.isfile(self.vocab_file   ):
								copyfile(self.vocab_file						,      lowercase   )
						elif not os.path.isfile(self.vocab_file   ):
								with open(lowercase						,      'wb'   ) as fi:
										A_						:							List[str]      = self.sp_model.serialized_model_proto()
										fi.write(lowercase   )

						return (out_vocab_file,)
				def     lowerCAmelCase_  (		self						,      lowercase						,      lowercase = None						,      lowercase = False   ):



						"""simple docstring"""





						if already_has_special_tokens:
								return super().get_special_tokens_mask(
								    token_ids_a=lowercase						,      token_ids_a=lowercase						,      already_has_special_tokens=lowercase   )

						A_						:							str      = [1] * len(self.prefix_tokens   )
						A_						:							Any      = [1] * len(self.suffix_tokens   )
						if token_ids_a is None:
								return prefix_ones + ([0] * len(lowercase   )) + suffix_ones
						return prefix_ones + ([0] * len(lowercase   )) + ([0] * len(lowercase   )) + suffix_ones
				def     lowerCAmelCase_  (		self						,      lowercase						,      lowercase = None   ):



						"""simple docstring"""





						if token_ids_a is None:
								return self.prefix_tokens + token_ids_a + self.suffix_tokens
						# We don't expect to process pairs, but leave the pair logic for API consistency
						return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens
				def     lowerCAmelCase_  (		self						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      **lowercase   ):



						"""simple docstring"""





						if src_lang is None or tgt_lang is None:
								raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'   )
						A_						:							str      = src_lang
						A_						:							Optional[Any]      = self(lowercase						,      add_special_tokens=lowercase						,      return_tensors=lowercase						,      **lowercase   )
						A_						:							Optional[Any]      = self.convert_tokens_to_ids(lowercase   )
						A_						:							Dict      = tgt_lang_id
						return inputs
				def     lowerCAmelCase_  (		self						,      lowercase						,      lowercase = "en_XX"						,      lowercase = None						,      lowercase = "ro_RO"						,      **lowercase						,      ):



						"""simple docstring"""





						A_						:							int      = src_lang
						A_						:							Any      = tgt_lang
						return super().prepare_seqaseq_batch(lowercase						,      lowercase						,      **lowercase   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						return self.set_src_lang_special_tokens(self.src_lang   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						return self.set_tgt_lang_special_tokens(self.tgt_lang   )
				def     lowerCAmelCase_  (		self						,      lowercase   ):



						"""simple docstring"""





						A_						:							Dict      = self.lang_code_to_id[src_lang]
						A_						:							int      = [self.cur_lang_code_id]
						A_						:							Union[str, Any]      = [self.eos_token_id]







				def     lowerCAmelCase_  (		self						,      lowercase   ):



						"""simple docstring"""





						A_						:							Optional[Any]      = self.lang_code_to_id[tgt_lang]
						A_						:							Union[str, Any]      = [self.cur_lang_code_id]
						A_						:							int      = [self.eos_token_id]







# flake8: noqa
# Lint as: python3
_UpperCAmelCase          =						[
    """VerificationMode""",
    """Version""",
    """disable_progress_bar""",
    """enable_progress_bar""",
    """is_progress_bar_enabled""",
    """experimental""",
]

from .info_utils import VerificationMode
from .logging import disable_progress_bar, enable_progress_bar, is_progress_bar_enabled
from .version import Version
from .experimental import experimental






